name: speak-incident-runbook description: 'Incident response for Speak API outages: triage, fallback to offline mode, and recovery procedures.

Use when implementing incident runbook,

or managing Speak language learning platform operations.

Trigger with phrases like "speak incident runbook", "speak incident runbook".

' allowed-tools: Read, Write, Edit, Bash(npm:), Bash(curl:), Grep version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io tags:

• saas
• speak
• api compatibility: Designed for Claude Code, also compatible with Codex and OpenClaw

Speak Incident Runbook

Overview

Incident response for Speak API outages: triage, fallback to offline mode, and recovery procedures.

Prerequisites

• Completed speak-install-auth setup
• Valid API credentials configured
• Understanding of Speak API patterns

Instructions

Step 1: Configuration

Configure incident runbook for your Speak integration. Speak uses OpenAI's GPT-4o for AI tutoring and Whisper for speech recognition.

// speak_incident_runbook_config.ts
const config = {
  apiKey: process.env.SPEAK_API_KEY!,
  appId: process.env.SPEAK_APP_ID!,
  environment: process.env.NODE_ENV || 'development',
};

Step 2: Implementation

// Core implementation for speak incident runbook
import { SpeakClient } from '@speak/language-sdk';

const client = new SpeakClient(config);

// CI test with mocked responses
async function runCITests() {
  const mockClient = new MockSpeakClient();
  await mockClient.assessPronunciation({ audioPath: "test.wav", targetText: "hello", language: "en" });
  console.log("CI tests passed");
}

Step 3: Verification

npm test

Output

• Speak Incident Runbook configured and verified
• CI pipeline with mocked Speak API tests
• Error handling and monitoring in place

Error Handling

Resources

• Speak Website
• OpenAI Realtime API
• Speak GPT-4 Blog

Next Steps

For deployment, see speak-deploy-integration.

Examples

Basic: Apply incident runbook with default settings for a standard Speak integration.

Production: Configure with monitoring, alerting, and team-specific language learning requirements.